Explore Workflows

View already parsed workflows here or click here to add your own

Graph Name Retrieved From View
workflow graph Running cellranger count and lineage inference

https://github.com/genome/analysis-workflows.git

Path: definitions/subworkflows/single_cell_rnaseq.cwl

Branch/Commit ID: 844c10a4466ab39c02e5bfa7a210c195b8efa77a
workflow graph wgs alignment with qc

https://github.com/tmooney/cancer-genomics-workflow.git

Path: definitions/pipelines/alignment_wgs.cwl

Branch/Commit ID: 233f026ffce240071edda526391be0c03186fce8
workflow graph bam to trimmed fastqs and biscuit alignments

https://github.com/genome/analysis-workflows.git

Path: definitions/subworkflows/bam_to_trimmed_fastq_and_biscuit_alignments.cwl

Branch/Commit ID: 389f6edccab082d947bee9c032f59dbdf9f7c325
workflow graph variant-calling-pair.cwl

https://github.com/mskcc/argos-cwl.git

Path: modules/pair/variant-calling-pair.cwl

Branch/Commit ID: 46eddf1e191352cad5e95dd3c24eeae3738da485
workflow graph Running cellranger count and lineage inference

https://github.com/genome/analysis-workflows.git

Path: definitions/subworkflows/single_cell_rnaseq.cwl

Branch/Commit ID: 10870aefd20469e728969269ff3c54b3b8339a18
workflow graph untar_reference_tar.cwl

https://github.com/kids-first/kf-alignment-workflow.git

Path: subworkflows/untar_reference_tar.cwl

Branch/Commit ID: 09c05e788df9cd77cead39892fd02140faa765a8
workflow graph Vcf concordance evaluation workflow

https://github.com/genome/analysis-workflows.git

Path: definitions/subworkflows/vcf_eval_concordance.cwl

Branch/Commit ID: 389f6edccab082d947bee9c032f59dbdf9f7c325
workflow graph diffbind-parallel.cwl

https://github.com/ncbi/cwl-ngs-workflows-cbb.git

Path: workflows/ChIP-Seq/diffbind-parallel.cwl

Branch/Commit ID: 33123d6a92bf0038951820d0d2c9cf501ae2ebf6
workflow graph Motif Finding with HOMER with random background regions

Motif Finding with HOMER with random background regions --------------------------------------------------- HOMER contains a novel motif discovery algorithm that was designed for regulatory element analysis in genomics applications (DNA only, no protein). It is a differential motif discovery algorithm, which means that it takes two sets of sequences and tries to identify the regulatory elements that are specifically enriched in on set relative to the other. It uses ZOOPS scoring (zero or one occurrence per sequence) coupled with the hypergeometric enrichment calculations (or binomial) to determine motif enrichment. HOMER also tries its best to account for sequenced bias in the dataset. It was designed with ChIP-Seq and promoter analysis in mind, but can be applied to pretty much any nucleic acids motif finding problem. Here is how we generate background for Motifs Analysis ------------------------------------- 1. Take input file with regions in a form of “chr\" “start\" “end\" 2. Sort and remove duplicates from this regions file 3. Extend each region in 20Kb into both directions 4. Merge all overlapped extended regions 5. Subtract not extended regions from the extended ones 6. Randomly distribute not extended regions within the regions that we got as a result of the previous step 7. Get fasta file from these randomly distributed regions (from the previous step). Use it as background For more information please refer to: ------------------------------------- [Official documentation](http://homer.ucsd.edu/homer/motif/)

 https://github.com/datirium/workflows.git

Path: workflows/homer-motif-analysis.cwl

Branch/Commit ID: 1f03ff02ef829bdb9d582825bcd4ca239e84ca2e
workflow graph scatter2.cwl

https://github.com/common-workflow-language/cwltool.git

Path: tests/wf/scatter2.cwl

Branch/Commit ID: 814bd0405a7701efc7d63e8f0179df394c7766f7